Sweep new customers off their feet for long-lasting relationships that feel so sweet (what can we say, welcome series optimization inspires our poetic side).

In our previous blog post, we talked all about customer retention, namely: why keeping existing customers is more cost- and time-effective than acquiring new ones, especially in the rapidly changing and highly competitive retail landscape. While a second or third purchase may look a lot like a first-time purchase in terms of value, each repeat purchase from an existing customer represents a return on the initial investment you made to acquire them — meaning that it’s actually worth much more to your retail organization in the long term.

Of course, maintaining customers means actively fostering relationships with them. In this article, we’ll take a deeper dive into the customer journey and examine how to keep high-value customers coming back for more, starting from the very first interaction.

Ensuring Customers Never Forget Their First

So, let’s say a new buyer has made their first purchase. Old wisdom dictates that this is the most impactful phase in a customer’s life cycle — the first date, the first impression, the big one. But it’s time to retire that idea; we’re big fans of the “second is best” philosophy. That’s because two-time buyers are nine times more likely to make another purchase than one-time shoppers — but guiding customers from that first purchase to the second can be just as difficult as securing the initial purchase.

Nobody knows for sure whether loyal, high-value customers are born or made. This question lies at the root of marketing’s great “nature versus nurture” debate: do marketers occasionally, naturally happen upon great customers, or do they nurture ‘Average Joes’ into becoming retail superstars? How much sway do marketers really have in ushering customers from their first purchase to their second?

It’s nearly impossible to know for sure; but that’s why the welcome series is such a critical component of any customer retention-focused marketing strategy. Getting off on the right foot with each and every new customer means leaving as little as possible up to chance.

Optimizing the Welcome Series

The welcome series, a relatively easy-to-set-up series of automated emails that introduces new customers to your brand, is your first opportunity to impress new buyers. Any welcome series is preferable to doing nothing at all, even if the series is the same every time, providing an overview of your brand and a roundup of popular products. Many marketers send the same email sequence to each new customer; it tends to go something like “brand intro,” “product categories,” “brand history,” and “loyalty program push.”

A generic welcome series like this is a good start to establishing more meaningful customer relationships, but marketers who are really looking to take it to the next level need to personalize the welcome experience. One simple way to do this is by personalizing the product recommendations in the welcome series emails. This means considering the customer’s first purchase and seeing what other customers who bought that same product also purchased, and making recommendations accordingly.

While product SKU personalization does help marketers craft a relevant message, the impact is relatively small. Fortunately, more can be done — with the right data. With the right tools and technology, customer segmentation requires a relatively low level of effort, but the payoff in terms of personalization potential (say that five times fast) is huge.

Let’s say you’re a shoe company with two types of customers: trendsetters and athletes. You obviously don’t want to put your creative team to work crafting a different email series for each and every new customer, but it’s feasible to create one athlete-focused series triggered by a first-time sneaker purchase and one trendsetter-specific series triggered by a stiletto purchase. The narratives in each series should leverage different creative assets, language, and tone — the increased relevance for the customer makes the initial creative investment more than worth it.

In our next blog, we’ll cover exactly what’s required to create those customer segments. If you can’t wait another second to find out more, you can download our full book, One and (Not) Done: Leveraging Customer Analytics to Address the One-Time Buyer Problem, here.

In the changing retail landscape, customer retention should take precedence over customer acquisition.

Ten years ago, e-commerce represented a new frontier for savvy retailers. Everywhere you looked in the digital wilderness, another brand was looking to stake their claim and connect with customers beyond the brick-and-mortar format. Growth was the name of the game: get new customers, and get them quickly and cheaply.

But in 2018, the digital retail landscape is more “war zone” than “wilderness”; discounts are up, profit margins are down, and each new customer acquisition is more time-consuming and expensive than the one before. To add to the challenge, these new customers just ain’t loyal. Attracting them might require a huge advertising push or offering a hefty discount, but they’ll be gone again as soon as a competitor offers a slightly better price. We call these consumers one-time buyers, one-and-dones, one-buy stands — well, you get the idea. They’re not coming back.

That’s why we propose that retailers direct their focus away from customer acquisition and towards customer retention. While bringing in a new shopper is great, it’s making them stay that counts in the long term.

Increasing retention by 5% can increase profits by 125%.

Customer Acquisition vs. Customer Retention

In the crowded online retail marketplace, it’s becoming more expensive to acquire new customers and less likely that they’ll stick around after the first purchase — which means that return on investment (ROI) is taking a big hit.

If the cost of bringing in a new customer is higher than the amount that new customer is predicted to spend with your company over time — well, you can do the math. That’s why many marketers have come to realize that customer retention is critical for long-term growth. A focus on acquiring new customers is unsustainable; cultivating existing buyers into long-term, repeat buyers is a much more cost-effective means of contributing to your brand’s overall health.

Furthermore, marketers can offset slow customer acquisition by retaining high value customers. A purchase from a repeat buyer looks an awful lot like a purchase from a new buyer, but it’s almost 7x more expensive to acquire a new customer than to keep an existing one — so, that repeat purchase is actually better for your bottom line.

In fact, no matter which way you look at it, turning existing customers into repeat customers is a good investment. Here are a few impressive numbers to prove it:

Clearly, a rock solid customer retention strategy is a vital element of any brand’s marketing stack — but creating one is easier said than done.

Optimizing Your Customer Retention Strategy

Customer retention begins with understanding each customer’s journey, from the limo to the final rose ceremony. The one (and only one) difference between retail and The Bachelor? The roses never have to stop coming — as long as marketers play their cards right.

Customers want personalization, and personalized communication begins by speaking effectively to customers at every stage of the marketing lifecycle: with a welcome series when they first come in contact with your brand, and by using consistent, relevant communication following purchases, you can successfully speak to customers when they’re fading or at-risk, and even when they’re presumed lost or “churned.”

An in-depth customer data platform can help you pinpoint exactly where each customer is in this process and set you up for success in attracting them, retaining them, and winning them back.

We’re going to take a deeper dive into lifecycle marketing in our next blog, so stay tuned. If you can’t take the anticipation, you can download our full book, One and (Not) Done: Leveraging Customer Analytics to Address the One-Time Buyer Problem, here.

Retailers already have access to all the customer data they need to attract — and retain and build — loyal customers. It’s just a matter of knowing how to use it.

Pro tip for telling the difference between retail marketers and dairy farmers: say the word “churn” and see how they react. In retail, churn is a dirty word; also known as “attrition,” it’s defined as the rate at which customers do not return for repeat purchases. Ever again. Sayonara, suckers.

Whatever a customer’s reasons for leaving your brand behind, the longer they’ve been gone, the lower the odds of ever winning them back. That’s why a lot of companies take measures to reel customers back in before they drift too far away — most commonly, these take the form of “We miss you” emails accompanied by a discount offer and coupons, which appear in a customer’s inbox after 90 days without a purchase.

But do they actually work? Short answer: no. Long answer: let’s imagine that customer A makes a purchase from you every single week for years, while customer B always buys around the holidays. By the time your 90-day email reaches customer A, they’ve skipped their regular purchase a dozen times — you’re way too late. But when you send customer B, who was all but guaranteed to make another purchase come holiday season, that “please come back” email, you’ve just offered up 10 or 25% off for no good reason.

Clearly, standard rule-based customer data strategies aren’t cutting it. But when your analytics teams are so bogged down with requests that their marketing teams have to wait three months or longer to get their questions answered, the type of personalized marketing that’s necessary to effectively retain a diverse range of customers is nearly impossible to achieve.

That’s why machine learning technology is proving to be indispensable to so many marketing teams. Machine learning models are tracking individual patterns to pick up on anomalies in behavior, indicating that the customer relationship is actually in danger, rather than relying on a one-size-fits-all approach to churn.

But while preventing churn is a huge step in the right direction for your brand (unless you’re selling butter or ice cream, in which case, awk), it’s actually just one of many ways that accurate, timely customer data can be implemented and turned into profit before Q4. And by many, we mean 11.

Achieve Better ROI:

Identify High-Value Customers

The top 5% of a company’s customer base can account for 30-40% of its total revenue, meaning that you need to know who these customers are — and make sure they stick around. It’s similar to the concept of incrementality that is being lauded as a new way to measure impact with regard to ad spends by marketers. Take a cue from leading men’s apparel brand Bonobos, who used predictive CLV analysis to identify its highest-value customers.

With that list in hand, Bonobos was able to implement low-cost but high-impact practices like including handwritten thank-you notes in these top customers’ shipments, ultimately increasing the predicted lifetime value of its customers by 20%.

Reduce Promotions

Many retailers feel so confident that a 15% discount will outperform a standard email that they’ll blast out a promotion to a 10,000-customer email list without testing a control group first.

While it might seem intuitive that including a discount will increase sales, it’s also possible that an email alone will be enough motivation for some customers to make another purchase. A lot of customers are highly motivated by promotions and coupons — but many are happy to pay full price, as long as they feel loyal to your brand. So, rather than offering a discount to a whole swath of customers, start small and test the outcome against a control group.

Increase ROI on Marketing Campaigns

For a lot of customers, direct mail can be an effective means of increasing repeat purchases. Tiffany & Co., for example, saw a significant increase in revenue with direct mail — but only after carefully targeting their mailing base. Obviously, you don’t want to send a bunch of flyers around to customers who are just going to (hopefully) recycle them immediately, but preemptively identifying which customers are likely to respond to snail mail can make it one of the most effective marketing tools in your arsenal.

98% of marketers agree that personalization helps advance customer relationships, however only 12% of marketers are satisfied in the level of personalization in their marketing efforts*

Improve Loyalty and Make Your Brand Relevant:

Personalization — to an Extent

In an ideal world, brands would have the marketing budgets and creative capacity to treat each of their customers like special flowers, with just the right water-to-plant food ratio for each. Unfortunately, that’s a little difficult to achieve in real life. With the right data, though, you can fake it until you make it.

98% of marketers agree that personalization helps advance customer relationships, however only 12% of marketers are satisfied in the level of personalization in their marketing efforts* — which means that with a little extra effort, your company can stand out. Breaking your customer base up into specific segments, understanding where they are in their journey from awareness to repeat buyer, and keeping easily-altered parts of your communication open to individualization are all ways to drive sustainable growth.

Predicted Product Affinities

Let’s go back to what we said about “keeping easily-altered parts of your communication open to individualization.” Predicted product affinities present one opportunity to do just that. If a customer makes a one-time purchase of a pair of yellow-and-red striped capris, it’s within your customer data wheelhouse to make the discovery that other customers who buy that product often also tend to go for your red foam nose, curly rainbow wig, and giant shiny shoes. Slide in those DMs — and by DMs, we mean your customers’ email inbox or Instagram feed — with suggested products that they’ll love, backed up by data.

Speak to Customers at Various Stages of the Funnel

Think of customers’ relationships with your brand as a funnel. The widest part of the funnel represents the largest group of consumers: those who are aware of your brand but haven’t interacted with it directly. As the funnel narrows, we get to the interested group; these people have perused your website but haven’t yet made a purchase.

Finally, the bottom point of the funnel is populated by your actual customers, whom you want to keep coming back for more. Most advertising channels let you utilize customer data for advanced targeting — take advantage of this feature to serve relevant ads to each group of consumers.

Increase Your Efficiency

Build Customer Segments in Seconds

The ability to discover and build customer segments is foundational to any marketing strategy — it’s how you predict whether an email promoting your new running shoes, your new ball gowns, or your new clearance item is most likely to attract the attention of a given customer. The more specific the segment, the more powerful your communication to that group will be.

To build these segments, you must have a sophisticated pattern-finding tool. Enter machine learning, which is all about picking up on patterns (a million times faster than a human could). Pair this advanced technology with your customer data, and you’re well on your way to segmentation that can cut through the noise and deliver results for your brand.

Measure Multi-Channel Marketing Holistically

Marketing teams think of Snapchat, Instagram, Facebook, and email as massively different beasts, but guess what? Your customers don’t. These platforms are all available to them on their phones as they go about their day, and the messages they receive from you on each contribute to their overall impression of your brand. Meanwhile, however, your brand is struggling to integrate the data that you glean from all of these different channels into one well-rounded portrait of a single consumer.

Customer data can be used to develop unified customer profiles and automate your campaigns to deliver consistent, highly tailored messaging to each.

Achieve Consistency

Remember your mother’s advice: “You’ll catch more flies with honey, but you won’t catch any flies if you mix honey and vinegar together. Sure, vinegar might be great in salad dressing, and honey might be great in tea, but salad and tea aren’t the same thing, kid.” Oh, just our moms?

What we’re trying to say is that your customer data can be used to develop unified customer profiles and automate your campaigns to deliver consistent, highly tailored messaging to each. This can help keep you from dousing your salad with honey, by which we mean accidentally advertising running shoes to your ball gown customers.

And Did We Mention…

Ease of Use

One of the biggest pain points that keeps marketers from effectively putting their customer data to use is the lag time between submitting a ticket with the analytics team and actually receiving the requested information. By the time the analytics team gets to your request for holiday shopping insights, you might be well into the new year and already looking towards spring clearance sales.

Marketer-friendly customer analytics platforms and quick testing mean that your analytics team can spend a lot less time crunching numbers and a lot more time helping the rest of your company figure out what those numbers actually mean — and how they can be translated into growth.

Integration into Marketing Tools

Close your eyes and imagine a world in which creating custom targeted ads is easy. Now open your eyes. Congratulations, your dreams are a reality.

One of the greatest pain points involved in creating Custom Audience ads and email campaigns is that they take two to three hours from start to finish, but direct integration with customer data to your email service provider (ESP), Facebook, and Google Ads means turning those hours into minutes. That’s huge — and that’s what’s possible with machine learning technology.

]]>https://www.custora.com/story/11-ways-customer-data-can-supercharge-q4-retail/feed/0https://www.custora.com/story/11-ways-customer-data-can-supercharge-q4-retail/The Marketer’s Guide to Predictive Analyticshttp://feedproxy.google.com/~r/CustoraBlog/~3/rTQ9b16Xw_k/ https://www.custora.com/story/the-marketers-guide-to-predictive-analytics/#respondThu, 26 Jul 2018 17:23:23 +0000https://www.custora.com/?p=6111We break down the basics of predictive analytics, its best practices in the world of retail, and explain how to apply the technology behind this “buzzword” to the real world.

In the business world, it seems like the more people talk about something, the harder it is to cut through the jargon and understand just what they’re getting at. Predictive analytics is an incredibly powerful and useful technology that unfortunately has become yet another business buzzword, a term used so often and across so many contexts that it becomes hard to understand what it really means.

So let’s break it down: what is predictive analytics, and how do we use it in retail?

What Predictive Analytics Is

Predictive analytics takes everything you know about your customers to date and applies statistical models to reliably forecast what will happen next. It sounds a little bit like magic, but it’s actually just math — though admittedly, it’s math that’s so complex and multi-layered that it can seem like magic to the untrained eye.

For retailers, predictive analytics allows you to infer what individual customers, customer segments, and your entire customer population will do in the future based on the information you have about what they’ve done in the past. Machine learning and probabilistic modeling are used to look at dozens of different variables and factor them into these predictions, searching for the variables that most reliably and consistently predict future outcomes.

Compare that with historical analytics, which uses trends in your recorded data over time to predict outcomes. A business can use historical analytics to understand which methods have brought the greatest success over time and use that understanding to inform future decisions.

Do these definitions sound a little similar? While both predictive and historical analytics use past data to predict future outcomes, the key difference is the level of complexity behind the predictions that each approach generates.

Let’s say that you wanted to use historical analytics to generate a weather forecast, for instance. You might see that the temperature today is 75°, and that the temperature yesterday was 74°. The day before yesterday it was 73°, and the day before that was 72°. Historical analytics would visualize that trend and lead you to the reasonable prediction that tomorrow it will be 76°.

But of course, there are many, many more factors that are much better predictors of weather than just last week’s temperature. This analysis wouldn’t even account for what time of the year it is, let alone barometric pressure, warm and cold fronts, or cloud patterns. Predictive analytics would account for all these factors and run hundreds of simulations to find the weather conditions that are most likely to play out tomorrow. Similarly, it can use a huge wealth of different information about your customers and their buying behaviors to identify just how likely they are to make purchases, which products they’ll most likely purchase, and when they’re most likely to purchase them.

What Predictive Analytics Isn’t

As you can imagine, predictive analytics is a pretty amazing and useful tool that can help retail marketers focus all their resources on the right customers at the right times with the right messaging. But since people in the business world tend to talk about it in an imprecise way, there is a misconception that predictive analytics can turn all your raw customer data into relevant insights with the push of a button. The reality is that predictive analytics is a tool like any other, and requires some effort and skill to be put to use effectively.

Predictive analytics is only useful if the insights it’s surfacing about customer behavior are relevant to your organization, but different organizations will have different ideas about what’s relevant. That definition of “relevant” will differ even further according to what position in the organization the user fills, what campaign they’re currently working on, what channels they’re using, and so on. One thing predictive analytics can’t predict is what you’ll need it for — that’s something that only the end-user can decide.

Furthermore, predictive analytics can only work with what you give it. Your analytics platform has to have access to all your raw data in order to generate insights from it, which means that members of your marketing team have to pull information from your CRM, ESP, and any other relevant sources to get the results they want. Luckily, if you’ve got a platform like Custora, all that stuff can be seamlessly integrated into custom dashboards without the need for much manual copying, pasting, and uploading from your marketing team.

Now that you have a solid understanding of what predictive analytics can do for you — and what it needs from you to do it — we can look into some simple best practices to guide how you apply this technology to your marketing campaigns for real results.

1. Ensure the predictive capabilities are purpose-built to answer mission-critical questions for retailers.

The information you pull from predictive analytics should be relevant for retailers. As we’ve said, what qualifies as relevant depends on any number of factors, so be sure to take the time and care to outline exactly what kind of insights you hope to generate from your analytics engine.

Regardless of your organizational or personal needs, one thing that’s true across the board for retail is that your analytics should be focused on solving customer-centric problems. For example, you’re probably going to be interested in knowing exactly when a particular shopper will make their next purchase and what the value of that purchase will be. Predicting that can be nearly impossible without the help of predictive analytics, because these relationships are so complex that only machine learning techniques will find them.

2. Use collected data to identify predicted “high-value customers.”

For a typical retailer, 50% of revenue is driven by just the top 10% of their customer base. You need to focus on and personalize this “high-value” segment in order to increase repeat purchase rate and cement loyalty.

Personalizing this segment has to go beyond what you already know about your average high-value customer. A predictive model should not only collect a large amount of data, but also dig deep to surface additional, unexpected insights into customer behavior and attributes. For example, your data might reveal a distinguishing behavior displayed by these MVP customers. By using this behavior to find lookalikes on Twitter and Facebook, you can produce insights on these shoppers that you never could have guessed from your CRM data alone.

3. Apply AI and machine learning to the real world.

You’re not using your top-of-the-line analytics engine to surface a list of quirky “fun facts” about your customers— you’re using it to look for new ways of improving campaign performance, keeping customers engaged, and increasing revenue. Keep your analytics focused on the real world.

Imagine you’re a retailer who’s worried about churn. You want to move the needle almost immediately after your high-value, loyal shoppers show the very first signs of slipping away. But how do you identify these customers, and how do you react quickly enough to keep their business?

Predictive analytics sounds great, and that’s because it is! Unfortunately, some marketers never get to see just how great it is because the data hasn’t been made accessible to them.

It’s a difficult question, because while there are a few obvious warning signs that a customer is slipping away, everybody has different ways of signalling they’re losing interest. But with predictive analytics, you don’t have to use a one-size-fits-all rule to identify customers at risk of churn. Your analytics can identify a baseline set of unique purchase tendencies for each high-value customer, then surface a segment of them every week who are veering from those patterns. Your marketers learn the early warning signs of churn, proactively send win-back messages, and take concrete steps to reduce attrition.

4. Data should be democratic — make sure your predictive analytics is accessible to the teams that use it.

Predictive analytics sounds great, and that’s because it is! Unfortunately, some marketers never get to see just how great it is because the data hasn’t been made accessible to them. Inaccessible data is useless data, and it represents a huge wasted opportunity for your brand.

That’s why any predictive analytics your marketing organization invests in needs to be configured in such a way that your marketers can easily access its data. That means not just that the insights it produces are understandable to individual marketers, but that they’re relevant, and can be turned into actionable strategies that are easy to read, execute, and measure. A great platform ensures that marketers within your organization have the ability to intuitively pull all the information they need from their analytics.

In Summary

The trouble with the buzzword-ification of predictive analytics isn’t that everybody’s excited about what it can do — we think that’s great, because it can do a lot of incredibly cool things! The problem is that the less clear people are on what predictive analytics really does and how it works, the more likely they’ll be flummoxed by it when it’s actually in their hands. We want marketers to leverage the full power of this technology, and to do that, they need to know what’s required of them to use it effectively.

Implementing predictive analytics into your everyday marketing activity isn’t a one-day process. It takes patience on the part of your team, some trial and error, and a willingness to learn new approaches to the age-old challenges of marketing. But the more you know about what to expect, the more quickly you’ll be able to apply today’s most advanced predictive technology to the work of keeping your customers happy and boosting your revenue.

It’s undeniable. There’s a shift happening in the market right now, and your customers are to blame.

Today’s consumers are channel-agnostic. They don’t think in terms of Facebook, Snapchat, email, website, etc. Rather, they think holistically about your brand and its products, and it’s time you start returning the favor.

The way business has been done in a channel-centric era can be summed up in three questions:

How do we market to our consumers?

What do we market?

Who do we market to?

Many marketers wouldn’t even bat an eye at this strategy. The channel-centric strategy puts the channel first, content second, and customer third.

The only problem? It’s backwards.

As we talk about in our post on segmentation vs personalization, the traditional method is failing marketers because they have to create multiple email variations for their different audience segments, which is causing severe problems with scalability, relevancy, and customer experience. Choosing what you market before who you market to completely ignores the needs, interests, and behavior of your customers.

The channel-centric strategy causes major disconnects in data, digital experiences, and integrated campaigns.

A customer-centric strategy for email marketing reverses the questions of the channel-centric strategy:

Who do we market to?

What do we market?

How do we market to our customers?

By focusing on who you market to before what you market, you put your customers in the center of your decision-making process. This gives you much more flexibility for the data you collect, what products you market, and orchestrating how you reach them.

Here’s five customer-centric and automated emails you can implement for your e-commerce or retail brand:

1. Browse Abandonment

Browse abandonment emails are one of the most effective, yet easy to get wrong, emails to send out to your customers. The basis of a browse abandonment is that a subscriber has visited a product page for a specified amount of time on your website and not taken action on it. While it seems highly scientific, it’s actually more of an art.

Think of browse abandonment emails as a coincidentally relevant and timely email rather than a creepy conversion tactic to capitalize on website activity.

Let me explain.

Blatantly revealing that you’re “watching” your customers’ every move and using that data to send them emails is downright creepy. Subject lines or email copy that include the specific product names are a surefire way to kill your subscriber’s motivation to any action on the email. So it’s not just about the science of incorporating browse data, product names, and advanced triggering logic. It’s about the art of knowing what to send, and when to send it.

Avoid:

Sending right away

Using product names or categories

Using symbols like $ or %

Using language like “We noticed…” or “Like what you saw?”

Do:

Wait at least several hours after they’ve ended their session on your website

Nonchalantly incorporate a discount in the body of an email

Use plain english and casual language

Use images of the browsed products

By waiting several hours after they’ve ended their session on your website before triggering the browse abandonment email, you avoid the risk of sending them email while they’re still shopping on your website or looking like you’ve been stalking their website activity. Casually incorporating a discount to seem like a coincidence is a much safer alternative to outrightly offering a discount on products you know they’ve viewed.

Think of browse abandonment emails as a coincidentally relevant and timely email rather than a creepy conversion tactic to capitalize on website activity.

2. Product Recommendations

Product recommendations is a feature that uses e-commerce data to programmatically serve relevant products in the body of an email. When using product recommendations in your email campaigns, it’s important to remember that the purpose of product recommendations is to engage with shoppers in a personalized way, NOT just to fill up space and hope something sticks.

The great thing about product recommendations is that they can be integrated into many different kinds of emails, such as browse abandonment emails, cart abandonment emails, transactional emails, welcome emails, and more.

Avoid:

Using broad user segments

Rigging the algorithm to focus on products you want to sell

Looking creepy or being too specific about what products you’re recommending

Do:

Identify specific segments

Use algorithms that make sense for your customers

Update your recommendations in real-time based on ongong data

Create a frictionless experience for customers to easily make a purchase

Make sure product recommendations are responsive, mobile-friendly and optimized for on all devices.

Use large, high quality images for each product to entice shoppers to view more.

Product recommendations are an excellent way to personalize each email experience for every individual shopper on your site. They’re also a great way to make email content relevant, enticing, and clickable. Personalized product recommendations to the right shoppers can be a transformative experience for your customers.

Here are some examples of how you can use product recommendations in your emails:

Display a mix of site-wide best sellers and recent top sellers to shoppers that browse your homepage but never make it any further into your site.

Display product recommendations (including best sellers) from the category the shopper was browsing to shoppers that click on and view a specific category, brand, or department but never actually view specific, individual products.

Display the exact product that the shopper viewed and then insert a mix of product-related best sellers and category-related best sellers as an upsell/downsell tactic to shoppers who have viewed specific, individual products on your site but did not actually add any of those products to their carts.

Display recommendations of top sellers within the category related to the search performed by the shopper to shoppers who have typed in a search term in your site search navigation yet did not go on to view any categories, products, or add anything to their carts.

Display the actual cart that the shopper left behind, fully populated with the products he added to his cart plus insert product and category-related best sellers as an upsell/downsell tactic to shoppers who have gone so far as to actually add a product or products to their carts.

Product recommendations can get fun (and tricky) when choosing where to display them in the email as well. Depending on the type and style of email, you could display one row with product-related recommendations, a row with category-related recommendations, or a row with general site-wide top sellers, or a combination of any of these three.

3. Welcome Series

A welcome email is an automated message sent to new subscribers or customers to welcome them and provide any interesting content or necessary information to set them up for success. It’s well-known that welcome emails are one of the most highly-opened emails.

Use the opportunity to immerse your subscribers into your world by making it easy to follow social accounts, familiarize themselves with the website and products, and provide an easy way back to the website.

Customers expect them. They open with them. And they engage with them.

Which makes them a great opportunity to exercise some customer centricity and show them that you care about them.

Avoid:

Making it about you

Being general

Being bland

Trying to push products right away

Do:

Make it about them.

Make an exclusive offer

Show personality

Show some useful tips and tricks for navigating the website

Use images or gifs

Use the opportunity to immerse your subscribers into your world by making it easy to follow social accounts, familiarize themselves with the website and products, and provide an easy way back to the website. It’s also the perfect opportunity to set expectations. The underlying reason why many people unsubscribe is not because they hate your brand now, didn’t like the emails, or even that they got too many emails — sometimes it’s simply mismatched expectations.

As a marketer, it’s easy to forget that subscribers may not know what they’re getting themselves into. You can see the automation and know how many emails they’re about to receive, but they have no idea.

Taking the time and transparency to tell subscribers what they can look forward to, expect to see in their inbox, and what to know is crucial. A healthy, engaged list is vastly better than a large, unengaged list.

4. Abandon Cart

Abandoned cart emails are sent to customers who have added products to their cart but failed to check out.

The Baymard Institute, an e-commerce usability think tank, has aggregated cart abandonment data from various industry sources over the last decade. However, despite major advancements in technology and e-commerce user experience design, the average cart abandonment rate has remained constant.

So instead of trying to eliminate the problem, see it as an opportunity to further engage with your customers. Sometimes, it’s not a problem with your website, product, or checkout, it’s just a matter of consumer behavior.

Taking a customer centric perspective, abandoned carts are a great opportunity to utilize customer behavior and data to create a fantastic experience and push them to complete checkout.

Avoid:

Waiting too long to send

Using pushy or passive-aggressive language

Do:

Have a customer service mindset

Design responsively, especially for mobile

Trigger in real time

Wisely use discounts

Abandoned cart emails are not a set-it-and-forget-it type of email. While it is automated, and you don’t have to fiddle with it, it’s best to think of it as a constant work in progress. Not testing or experimenting with your emails is leaving money on the table. Consistent testing can string together many small wins and a big increase in revenue generated. Test content types, subject lines, CTAs, layout, and images.

5. Back In Stock

Products inevitably go out of stock. Displaying low inventory to create urgency or selling limited-time products will always go out of stock. But you don’t have to turn away visitors who missed out, thanks to back in stock email alerts.

Instead of a visitor landing on a product page, reading that it’s out of stock, and then leaving the page, you now have an opportunity to fill that demand. Conversely, when someone lands on a product page and sees that it’s out of stock, a popup or embedded form on the page can capture their email, send them an email when it’s back in stock, and convert the visitor into a paying customer.

Avoid:

Hiding the back in stock alert CTA in an obscure location on the page

Offering a discount for their email

Falsely displaying an item as out of stock

Sending promotional emails to users who only opted in to the back in stock alert

Do:

Use targeting to display a popup at the right time

Place an embedded form in an easy-to-see location on the page

Protect against spammy emails

Do you make your customers wait until they get to the checkout to break the bad news? Eliminate the chance for a bad experience with your brand and use back in stock alerts to put the customer first.

Implementing a full customer-centric marketing strategy for a channel-agnostic customer doesn’t happen overnight. It requires organizational changes, new processes, other tools and platforms.

In Summary

When moving towards an integrated customer perspective in marketing, and email marketing specifically, it quickly becomes obvious that this also impacts the way brands organize their internal processes too. Email marketers, content marketers, web analytics experts, CRM practitioners, social media marketers, etc., all have to collaborate in order to achieve a single view and customer-centric approach.

Implementing a full customer-centric marketing strategy for a channel-agnostic customer doesn’t happen overnight. It requires organizational changes, new processes, other tools and platforms. But you can start with these 5 automated emails to amp up your customer centric email program.

If you want to learn more about how to do more with less, use all your data, and do customer centric email marketing, visit us at Cordial.com or read more content like this on the Cordial blog.

]]>https://www.custora.com/story/5-customer-centric-email-automations-you-can-trigger-with-your-e-commerce-data/feed/0https://www.custora.com/story/5-customer-centric-email-automations-you-can-trigger-with-your-e-commerce-data/Marketing to Generation Z: How to Appeal to the Next Consumer Powerhouse (Part 2)http://feedproxy.google.com/~r/CustoraBlog/~3/LJWAy42fAWk/ https://www.custora.com/story/marketing-to-generation-z-how-to-appeal-to-the-next-consumer-powerhouse-part-2/#respondThu, 28 Jun 2018 14:35:28 +0000https://www.custora.com/?p=6091

Generation Z is a rising consumer powerhouse. Estimated at two billion globally, they are forecasted to account for 40% of all consumers by 2020.

However, Gen Z is a deeply divided group with unique characteristics, very distinct feelings, ambitions, and rituals. Therefore, it is crucial for retail marketers to develop a deeper understanding from a demographic and psychological standpoint to cement their loyalty and leverage their spending power.

In part one of this blog we spoke to Cassandra Napoli, Digital Media & Marketing Editor at WGSN about the concerns, influences, buying behavior and trends of Gen Z.

Our conversation continued as we took a deeper dive into how marketers can bridge the divide and attract both sides of the spectrum, the importance of effectively testing and measuring the effectiveness of your marketing messages, and the best ways retail stores can stay relevant to Gen Z in the ‘Age of Amazon’.

Hi Cassandra, we previously discussed the two segments within Gen Z — the style-driven segment known as ‘Gen Me’, and their action-oriented counterparts, ‘Gen We’. Considering their different beliefs, trends, and influences, how can marketers attempt to bridge the gap and appeal to both sides of the spectrum?

Despite Gen Me and Gen We living on polar opposite sides of the spectrum, there are a group of influencers that manage to bridge the divide between the two cohorts. Broken down into four categories—celeb, mass, micro and mock—these accounts are able to float between both sides, appealing to all.

On the celebrity forefront is Rowan Blanchard — a style-driven 16-year-old with a Gen Me aesthetic, who simultaneously uses her platform for good. At age 13, she penned a letter on intersectional feminism.

On the mass side, there’s Emily Elaine Oberg, who is a content creator and streetwear figure who posts selfies beside meaningful messages of sustainability. On the micro front is Sophia Hadjipanteli, who is a selfie-loving Gen Me with very unique facial characteristics. She proudly sports her bold unibrow, redefining beauty standards by embracing vulnerability online.

And finally, there’s mock influencer Lil Miquela—a computer simulated CGI avatar who aesthetically looks the part of any other contoured Gen Me. Where she differs though, is with her roots in activism, advocating for a variety of important causes.

Real time access to analytics that measure the effectiveness of your campaigns will indicate whether you are communicating well within the segments you are targeting and will help craft the perfect communication strategy.

It is also important to acknowledge that customers with the same demographics might have different purchase tendencies. What advice do you have for marketers that are testing their messages to either the Gen Me or Gen We audience?

By developing a deeper understanding of what will resonate with Gen Z, you can start tailoring your marketing campaigns and messaging. However, whether you are marketing to Gen Me, Gen We, or both, we can’t just assume you are effectively speaking to all customers of a certain cohort. Using a customer analytics platform that can give you insights into purchase cadence, product and channel preferences becomes a very important part of your marketing strategy. Real time access to analytics that measure the effectiveness of your campaigns will indicate whether you are communicating well within the segments you are targeting and will help craft the perfect communication strategy.

One way to capture the fickle Gen Z audience is to offer up a social gift — an Instagram-worthy sharable moment that will give your brand increased notoriety.

Amazon is a popular topic in the retail world. It has rapidly evolved shopping behavior and is predicted to capture nearly 10 percent of total retail sales by 2020. It is also seen as one of the reasons people are spending more online and less in stores. How can retail stores stay relevant to Gen Z in the age of Amazon?

Retail is in a state of flux right now and brands are scrambling to figure out the right solution to lure customers into the stores and to spend their money. To no one’s surprise or shock, one way to capture the fickle Gen Z audience is to offer up a social gift — an Instagram-worthy sharable moment that will give your brand increased notoriety, while giving consumers value and status amongst/within their own communities.

Designing for Instagram extends beyond beautiful fixtures and displays within a store. Having a share-worthy highly identifiable space that is synonymous with your brand is critical to winning over this cohort (think Glossier’s showroom or the Barneys New York Downtown staircase that rippled across social media when it first opened). Colour is also critical and drives audiences in (think Mansur Gavriel’s pastel-hued boutique spaces). This phenomenon permeates across industry — from food and fashion to beauty and tech.

Another way to succeed is launching special interactive, Insta-friendly brand activations that build hype online and draw large crowds in (turn to The Museum of Ice Cream as a case study worth noting). In the study we say, ‘don’t chase culture, create it’ – and I think this line holds real value here.

Other retailers like Supreme are thriving, despite Amazon. The long queues outside their stores have indirectly created a type of Gen Z ‘community’, in which the line serves as a place to build connections in a judgement-free zone. However, I think it could be dangerous if others attempt to recreate the ‘Supreme effect’. As much as a brand will try, very few will achieve the same level of hype and success as that of Supreme. They are perhaps the case study of all case studies, mastering the art of exclusivity. But very few brands will be able to mirror what they have managed to do. If stores want to become the premier destination for teenagers to congregate, they should offer up something truly special and unique that attracts kids and encourages them to stay put once there.

Interested in learning more about Gen Z? Read the WGSN white paper here.

To learn more about Custora and how we can help you personalize your messaging and effectively measure the impact of your marketing campaigns, request a free demo here.

It’s no secret that consumers are now expecting a more personalized experience. To achieve personalization at scale, marketers need to be able to organize their data and leverage customer insights. Yet, it can become challenging to prioritize the overwhelming amount of data, extract the right customer traits, and then use this information to execute campaigns that will really drive results.

In this webinar, Custora teams up with Bounce Exchange to build your behavioral playbook. We strip it back to understand exactly what a single-customer view is, the benefits of behavioral segmentation and relationship marketing, the best ways to personalize campaigns, and how to effectively move the customer through the funnel.

]]>https://www.custora.com/webinar/building-marketing-campaigns-using-a-single-customer-view/feed/0https://www.custora.com/webinar/building-marketing-campaigns-using-a-single-customer-view/Marketing to Generation Z: How to Appeal to the Next Consumer Powerhouse (Part 1)http://feedproxy.google.com/~r/CustoraBlog/~3/qqQpKI9VEqw/ https://www.custora.com/story/marketing-to-generation-z-how-to-appeal-to-the-next-consumer-powerhouse-part-1/#respondWed, 20 Jun 2018 17:18:36 +0000https://www.custora.com/?p=6077

Gen Z is set to become the most crucial generation to the future of retail. Defined as those born between 1995 and 2010, the demographic estimates at two billion globally and the vast majority are just years away from full financial independence.

Most retailers are familiar with the general behavior of Gen Z consumers. They are seen as tech-obsessed and focused on building their own personal brand. However, retailers need to set aside their preconceptions and stereotypes to successfully capture their attention. There are major opportunities to leverage the spending power of Gen Z, but without empathy and understanding, brands risk being dismissed as insignificant.

It is no longer just about selling items that feed into self-interests or relying on celebrity influencer marketing. There is another side to Gen Z that retailers need to consider. Developing a deeper understanding from a demographic and psychological standpoint is key to cementing loyalty from both sides of the spectrum.

We spoke with Cassandra Napoli, Digital Media & Marketing Editor at WGSN about the concerns and influences of Gen Z, the two micro-segments identified within this generation, and how marketers can bridge the gap to create authentic and lifelong connections with Gen Z consumers.

Hi Cassandra, tell us a little bit about WGSN and what you do there.

WGSN is the leading global trend forecasting authority currently celebrating its 20th year in business. I write for WGSN Insight, the consumer and market intelligence platform which launched back in October 2016. I cover the media and marketing vertical and am responsible for scouring the globe in search of the latest and greatest trends that represent the very best ways brands are communicating with their customers from out-of-home (OOH) to social media, and everything in between.

“This cohort is multifaceted with very distinct feelings, ambitions and rituals.”

You recently spoke directly to 16 – 21 year olds with diverse backgrounds from all over the world to get a true insight into their lives; what surprised you most about this generation?

Conducting a focus group has really helped us to identity how problematic it is to simply bucket Gen Z under one blanket description. This cohort is multifaceted with very distinct feelings, ambitions and rituals. At the same time, it’s crucial to understand that there are two cohorts under the Gen Z umbrella and they are not so cut and dry, ‘Gen Me’ and ‘Gen We’. Both segments are deeply divided, but that’s not to say they are incapable of seeing each other’s sides and opinions. In fact, it’s quite the opposite. Gen Z’s fluid nature enables them to acknowledge and listen to the other side’s arguments and beliefs, free flowing along the spectrum and — either self-willing or unconsciously — contradicting themselves.

“Gen Z’s fluid nature enables them to acknowledge and listen to the other side’s arguments and beliefs, free flowing along the spectrum and — either self-willing or unconsciously — contradicting themselves.”

You mention two segments — ‘Gen Me’ and ‘Gen We’. Can you briefly explain the differences between the two and why this is important for retail marketers to understand?

While we say they are deeply divided, with unique characteristics, they are a fluid bunch that understands each other and the many contradictions that encompass them.

To make matters simple, you might want to revert over to our Me to We infographic our latest white paper. For example, Gen Me are a selfie-obsessed group that have a similar look to them which stems from the Instagram effect, meaning: the camera is most critical. On the other hand, Gen We are looking to use their voices to speak up and out both online and in real-life settings, meaning: the keyboard would service them more.

Gen Me uses social as a path to escape from the pressures of reality, while Gen We are more rooted in optimism, using social media to advocate for the change they wish to see. Retail marketers need to understand that:

‘Gen Me’ is already documented and marketed to by the majority of brands. They are the larger sector within the Gen Z cohort, driven by style and status. They essentially have two identities —- their true selves and the glossy and filtered version of themselves that they share online. But that’s not to say they are not in touch with reality. This group is entrepreneurial-minded and they’re self-starters, effectively monetizing their interests and passions into full-fledged businesses —- from reselling and beauty tutorials to cryptocurrency and video game live streaming. They are standing in line in the name of exclusivity, flocking to retail stores and restaurants that serve as ‘Instagram bait’. They are also going to ‘cons’ (i.e Sneaker Con, Beautycon) and festivals to capture a photo that gives them bragging rights within their community. For this group, if it wasn’t captured for social, it never actually happened.

‘Gen We’ are their progressive, empowered and action-oriented counterparts who believe caring is cool and advocate for issues such as mental health, sustainability and inclusivity. They’re change-agents who are unapologetic when it comes to rallying for the important causes, facing difficult matters head on, rolling up their sleeves, and going to work. Simultaneously, their relationship with social media differs from that of Gen Me. They are champions of imperfection and vulnerability, using social messages to create a more accepting and inclusive environment online. Rather than aspiring to be like someone else, they are looking laterally, influencing one another in their decisions to speak up and out.

Gen Z makes up a quarter of the U.S. population and is forecasted to account for 40% of all consumers by 2020. What are some examples of the current buying behavior trends you have seen within this generation and how might it evolve?

Driven by capitalism and hypnotised by hype, Gen Me teens have opted to monetise their interest in streetwear. Willing to wait online to get access to the latest and greatest exclusive product, teens are gaining access to merch and turning around to flip it either IRL or via online marketplaces almost instantaneously. The seasonal summer job has come and gone. Today, teens are earning large sums of money from these seasonless reselling operations.

The personal brand is paramount, and the face has thus become the most important entity for modern Gen Me teens. Looking to be classed as cool and achieve the unobtainable level of perfection that Instagram breeds, these kids are looking to achieve the coveted look as they expand the filter bubble with a stream of selfies and Snaps. This image-obsessed group is contributing to a surge within the beauty industry, with teens spending $368 annually on beauty products.

On the flip side of the spectrum lie Gen We teens, who are embracing this new notion of ‘buycotting’. Rather than boycott the brands they deem controversial, they are deliberately buying into those brands they believe in and that share similar values and principles to their own.

Many retailers strive to understand their customers on a deeper level, but this becomes challenging when their employee base does not reflect their customer base. From your research, which marketing messages will most likely resonate with Gen Z?

Gen Me are rooted in escapism, running away from the troubles and anxieties of life by leaning on social media platforms. They are, indeed, style-driven, operating at the mercy of popular online tastemakers who cultivate this unobtainable lifestyle that Gen Me aspires to. If there is anything driving this image-obsessed group to convert, it’s creating shareable moments at scale. Marketers must resonate with the zeitgeist of this group by creating IRL moments that serve as social currency online.

“It’s really all about understanding how to tap into Gen We, which is crucial for marketers today.”

As stated earlier, Gen Me is the majority of Gen Z consumers and so a lot of the marketing messages out there are currently resonating and helping to drive the endless stream of content. It’s really all about understanding how to tap into Gen We, which is crucial for marketers today.

I think it’s important to note that from a marketing perspective, no brand really exists that does a nice job of speaking exclusively to Gen We. While this presents a clear opportunity, authenticity is key. Sustainability, compassion, self expression and collaboration seem to be all separate causes that marketers could potentially tap into in order to reach this group. But it’s critical to note that Gen We will be able to suss out pure capitalistic motives that derive from ill intentions. Marketers must be conscious not to sensationalize movements or marginalize people in the name of making money. Embracing important causes must be done in a manner that is tasteful and rooted in truth otherwise, Gen We will boycott your brand, which will be difficult to come back from.

Stay tuned…

Stay tuned for part two of our conversation with WGSN as we discuss the ways marketers can bridge the gap and appeal to both sides of the spectrum, and how retail stores can stay relevant to Gen Z in the age of Amazon. For more info, download the WGSN white paper here.